Method of administering a mutual fund that seeks to provide regular monthly payments without consuming principal

ABSTRACT

A method of administering an investment fund. The method includes the steps of creating shares for sale, providing a managed distribution schedule identifying a number of payments to be provided during each of consecutive periods, providing an investment strategy for investing in assets to provide funds sufficient to meet the managed distribution schedule, issuing a share to an investor in exchange for funds received from the investor, investing the received funds according to the investment strategy, calculating the value of each of the payments to be provided according to the managed distribution schedule in a period to the investor, and providing each of the payments to the investor during the period. Each payment is calculated according to a formula that specifies that the value of each payment is based on a trailing Net Asset Value (NAV) of the investor&#39;s share.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority from U.S. Provisional Application No. 60/993,746, filed Sep. 14, 2007, the contents of which are herein incorporated by reference in their entirety for all purposes.

BACKGROUND OF THE INVENTION

Many investors arrive at retirement with substantial assets accumulated over years of disciplined saving and prudent investing. Often, these investors are concerned about how best to use their assets to meet monthly retirement expenses, while at the same time preserving their assets for heirs, philanthropy, or other purposes. Traditionally, these investors have had three basic options for generating retirement income:

1. A “planned withdrawal program,” in which an investor gradually spends a limited portion of assets over a set period, with the remaining assets invested for long-term retirement goals.

2. A “guaranteed income option,” in which an investor turns over assets to an insurance company and purchases a fixed immediate annuity that provides guaranteed income for life.

3. A “spend only the income strategy,” in which an investor spends only the dividend and interest income generated by his or her retirement portfolio, leaving the principal intact.

SUMMARY OF THE INVENTION

According to one aspect, the present invention includes an embodiment of a method of administering an investment fund. The method includes the steps of creating a plurality of shares in the investment fund for sale, providing a managed distribution schedule identifying a number of payments to be provided during each of a plurality of consecutive periods, providing an investment strategy for investing in assets to provide funds sufficient to meet the managed distribution schedule, issuing at least one share to an investor in exchange for funds received from the investor, investing the received funds according to the investment strategy, calculating the value of each of the payments to be provided according to the managed distribution schedule in a period, and providing each of the payments to the investor during the period. The managed distribution schedule includes a formula for calculating a value for each of the payments in the period. The formula specifies that the value of each payment equals 1/nth of a predetermined percentage of a designated value corresponding to one of the plurality of shares. The number, n, equals a number of payments to be made in the period, and the designated value equal a trailing Net Asset Value (NAV).

According to another aspect, the present invention includes another embodiment of a method of administering an investment fund. In this other embodiment, the method includes the steps of creating a plurality of shares in the investment fund for sale, providing a managed distribution schedule identifying a number of payments to be provided during each of a plurality of consecutive periods, issuing at least one share to an investor in exchange for funds received from the investor, investing the received funds in assets including cash, securities, derivatives and other investments, and providing payments to the investor in a period according to the managed distribution schedule. The managed distribution schedule includes a formula for calculating a value for each of the payments. The formula specifies that the value for each payment in the period equals 1/nth of a predetermined percentage of a designated value corresponding to one of the plurality of shares. The number, n, equals a number of payments to be made in the period, and the designated value equals a trailing Net Asset Value (NAV).

BRIEF DESCRIPTION OF THE FIGURES

The invention is understood from the following detailed description when read in connection with the following figures:

FIG. 1 illustrates an investment fund comprising an investment portfolio, in accordance with an embodiment of the present invention;

FIG. 2 illustrates a flow diagram of a method of constructing and managing the fund illustrated in FIG. 1, in accordance with an embodiment of the present invention;

FIG. 3 illustrates a flow diagram of a method of constructing and managing an investment portfolio of the fund illustrated in FIG. 1, in accordance with an embodiment of the present invention;

FIG. 4 illustrates an exemplary plot of the probabilities of various investment funds of maintaining real spending power after 20 years versus the probabilities of payments made by such funds declining by 5% from one year to the next, in accordance with an embodiment of the present invention;

FIG. 5 illustrates a capital markets model employed by the method illustrated in FIG. 3, in accordance with an embodiment of the present invention; and

FIG. 6 illustrates exemplary distributions of outcomes generated by simulations of the capital markets model illustrated in FIG. 5 for selected asset classes, in accordance with an exemplary embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

Retirees generally have two basic needs in retirement funds:

(1) regular monthly payments to help meet retirement expenses, and (2) the preservation of retirement savings for future use.

Referring now to FIG. 1, there is illustrated an investment fund 100 comprising an investment portfolio 110 and a plurality of shares 120. Portfolio 110 comprises a plurality of securities and other investments (collectively referred to herein as “securities”). The securities may comprise any of stocks (e.g., U.S. stocks or foreign stocks, such as emerging-market stocks), bonds, commodity futures, inflation-indexed securities (e.g., Treasury Inflation Protected Securities (“TIPS”)), shares in real estate investment trusts (“REITs”), hybrid securities, currencies, options on securities or securities indexes, futures contracts, options on futures contracts, credit default swaps, total return swaps, forward foreign currency agreements and other derivatives. The securities in portfolio 110 may further comprise shares in one or more funds, such as stock funds, funds that track the Europe, Australasia, and Far East (“EAFE”) Index, funds that track the Lehman Aggregate Bond Index, commodities funds, money market funds, equity market neutral funds, absolute return funds, etc. In embodiments of fund 100 where portfolio 110 includes shares in one or more investment funds, fund 100 may be described as a “fund of funds.” It is understood that the descriptor, “fund of funds,” however, does not exclude fund 100 from owning other types of securities directly. Thus, fund 100 may be characterized as a “fund of funds” even while owning stock, bonds, futures, etc. directly in portfolio 110.

In the embodiment of fund 100 illustrated in FIG. 1, portfolio 110 includes one or more U.S. stocks, one or more emerging market stocks, one or more shares in one or more EAFE Index funds, one or more shares in one or more Lehman Aggregate Bond Index funds, cash, one or more TIPS, one or more shares in one or more REITs, one or more commodity-linked instruments, one or more shares in one or more equity market neutral funds, and one or more shares in one or more absolute return funds. Fund 100 is formed and managed by a fund administrator (not illustrated).

Referring now to FIG. 2, there is illustrated a method 200 for constructing and managing fund 100 and providing payments to shareholders, in accordance with an exemplary embodiment of the present invention. Method 200 begins with a step 210 of establishing a managed distribution policy of fund 100 at the inception for fund 100. More specifically, in step 210, fund 100, or more specifically the administrator of fund 100, establishes a managed distribution policy (also called a “payment schedule”) to determine how payments of fund 100 are to be calculated, sourced and distributed to shareholders in fund 100 over the life of fund 100. Method 200 continues to a step 220 in which the administrator of fund 100 establishes investment objectives, investment strategies and performance targets for fund 100 to allow fund 100 to achieve its managed distribution policy.

The investment objectives, investment strategies, performance targets, and the managed distribution policy of fund 100 determine how fund 100 is structured and managed. Generally, the administrator chooses the investment objectives, investment strategies, performance targets, and managed distribution policy to allow fund 100 to operate to the extent possible without consuming capital.

Several exemplary embodiments of fund 100 are described herein. In each of the several embodiments of fund 100, the specifics of the investment objectives, investment strategies, performance targets, and managed distribution policies differ as follows:

In a first embodiment of fund 100 (herein “Fund A”), the administrator of fund 100 seeks to generate total returns sufficient to sustain a managed distribution policy while providing inflation protection and capital appreciation over the long term. The managed distribution policy of Fund A is based on an annual distribution rate equal to 3%. Thus, the investment objective of Fund A is to seek to make monthly distributions of cash while providing inflation protection and capital appreciation over the long term, and the investment strategy is tailored to achieve this investment objective.

In a second embodiment of fund 100 (herein “Fund B”), the administrator of fund 100 seeks to generate total returns sufficient to sustain a managed distribution policy while providing inflation protection and capital preservation over the long term. The managed distribution policy of Fund B is based on an annual distribution rate equal to 5%. Thus, the investment objective of Fund B is to seek to make monthly distributions of cash while providing inflation protection and capital preservation over the long term, and the investment strategy is tailored to achieve this investment objective.

In a third embodiment of fund 100 (herein “Fund C”), the administrator of fund 100 seeks to generate total returns sufficient to sustain a managed distribution policy while preserving capital over the long term. The managed distribution policy of Fund C is based on an annual distribution rate equal to 7%. Thus, the investment objective of Fund C is to seek to make monthly distributions of cash while providing capital preservation over the long term, and the investment strategy is tailored to achieve this investment objective.

Although method 200 indicates the flow of the method progressing from step 210 to step 220 (the flow being indicated by the arrow extending from step 210 to step 220), it is contemplated that steps 210 and 220 may be performed in any order. Thus, the administrator of fund 100 may establish a managed distribution policy for fund 100 at its inception in step 210 and then develop investment objectives, investment strategies and performance targets for fund 100 in step 220 to satisfy the managed distribution policy, or the administrator of fund 100 may establish investment objectives, investment strategies and performance targets for fund 100 in step 220 and then develop a managed distribution policy in step 210 to make distributions resulting from the investments of fund 100. Furthermore, although method 200 indicates that the investment objectives, investment strategies and performance targets are developed in one step (step 220), it is contemplated that the investment objectives, investment strategies and performance targets may each be developed in separate sub-steps.

The Managed Distribution Policy of Fund 100

The managed distribution policy of fund 100 generally provides for the periodic distribution of a targeted amount of cash (payments) to be made to shareholders during each of a plurality of consecutive periods based on (1) a distribution rate specified in the managed distribution policy of fund 100 and (2) prior performance of fund 100. The managed distribution policy provides for a number of payments to be provided during each of the consecutive periods and contemplates that the payments are fixed and are of equal amounts in each of the periods, unless there are one or more additional distributions made sometime during a period. As described below, the distributions per share vary from period-to-period based on the prior performance of fund 100.

The managed distribution policy sets forth rules for calculating the payments to be made in each of the consecutive periods for each share 120 of fund 100. More specifically, the managed distribution policy specifies a formula that determines how dollar amounts of the payments are to be calculated in the future based on the distribution rate and the prior performance of fund 100 and how such payments are to be distributed in the future. Due to market volatility, fund 100 does not specify, at the inception of fund 100 or at any time thereafter, dollar amounts to be provided for the payments in the consecutive periods. In other words, fund 100 does not guarantee any amounts of payments to be distributed.

Payments to be provided during each of the consecutive periods in the future are to be calculated during each of the consecutive periods or in a period immediately preceding each of the consecutive periods. In one exemplary embodiment, the calculations during the consecutive periods are to be completed at the beginnings of the consecutive periods.

In an exemplary embodiment of the managed distribution policy, the prior performance of fund 100 is quantified by a trailing net asset value (herein “NAV”) of each share 120 in fund 100. The trailing NAV for each share in fund 100 is calculated by averaging the NAV of each share in fund 100 over a predetermined period of time preceding the time of calculation. Because the NAV is calculated for a predetermined period of time preceding the time of calculation, the NAV is referred to as a “trailing NAV.”

In this exemplary embodiment, the managed distribution policy provides for the calculation of per-share payments made by fund 100 to be based on the trailing NAV (in addition to the distribution rate). More specifically, the managed distribution policy provides that the amount of each payment to be made in each of the consecutive periods is to be calculated to equal 1/nth of a predetermined percentage of the trailing NAV of each share in fund 100, as represented in the following formula:

$\begin{matrix} {{{{Distribution}\mspace{14mu} {per}\mspace{14mu} {Share}} = {\frac{{Predetermined}\mspace{14mu} {Percentage}}{n} \times {Trainling}\mspace{14mu} N\; A\; V}},} & (1) \end{matrix}$

where the value “n” is to equal the number of payments to be made in each of the consecutive periods defined by the payment schedule and the “predetermined percentage” is the distribution rate identified in the managed distribution policy. The predetermined percentage (distribution rate) may, for example, be one of 3%, 5%, or 7%, respectively corresponding to embodiments of fund 100 as Fund A, Fund B, and Fund C.

Because the payments of fund 100 are actually calculated in the future, i.e., at some time after the inception of fund 100, and are based on prior performance of fund 100, e.g., the trailing NAV of each share in fund 100, the distributions per share may vary from one of the consecutive periods to another as the performance, e.g., daily NAV, of fund 100 varies over time.

In an exemplary embodiment of fund 100, each of the consecutive periods identified by the managed distribution policy is a fiscal year, and the managed distribution policy identifies that the payments made during each of the fiscal years are to be made monthly. In such an embodiment, the managed distribution policy directs that the monthly distributions per share are to be calculated at the beginning of each fiscal year by averaging a per-share NAV of fund 100 over a prior three-year period of fund 100 in order to increase the relative predictability and relative stability of the distributions of fund 100 to shareholders from year-to-year. A modified version of the formula is to be used until fund 100 has established three years of history. Thus, at the beginning of the first year of fund 100, each of the monthly payments to be provided in the first year is to be calculated using an initial per-share value of fund 100; at the beginning of the second year of fund 100, each of the monthly payments to be provided in the second year is to be calculated using averaged daily per-share NAVs of fund 100 over at least a portion of the first year of fund 100; and at the beginning of the third year of fund 100, each of the monthly payments to be provided in the third year is to be calculated using averaged daily per-share NAVs of fund 100 over at least a portion of the first and second years of fund 100. At the beginning of the fourth year and subsequent years of fund 100, each of the monthly payments to be provided in the fourth and subsequent years is to be calculated using averaged daily per-share NAVs of fund 100 over the three years previous to the year for which the calculations are to be made.

In another exemplary embodiment of fund 100, the distributions per share may be calculated in view of a hypothetical account of a hypothetical shareholder of fund 100 assumed to hold shares in fund 100 purchased at inception. For purposes of the calculation of per-share payments made by fund 100, the hypothetical account is assumed to experience the same distributions as the accounts of actual shareholders of fund 100 and that no further purchases or redemptions are made for the hypothetical account except by way of the automatic reinvestment of any and all additional distributions in additional shares in fund 100. More specifically, in this exemplary embodiment of fund 100, the managed distribution policy provides that the amount of each payment to be made in each of the consecutive periods is to be calculated to equal 1/nth of a predetermined percentage of the average daily value of the hypothetical account over a specified period of time, as represented in the following formula:

$\begin{matrix} {{{{Distribution}\mspace{14mu} {per}\mspace{14mu} {Share}} = {\frac{{Predetermined}\mspace{14mu} {Percentage}}{n} \times \frac{\begin{matrix} \begin{matrix} {{Average}\mspace{14mu} {daily}\mspace{14mu} {account}\mspace{14mu} {balance}} \\ {{of}\mspace{14mu} {hypothetical}\mspace{14mu} {shareholder}} \end{matrix} \\ {{over}\mspace{14mu} {this}\mspace{14mu} {period}} \end{matrix}}{X}}},} & (2) \end{matrix}$

where the value “n” is to equal the number of payments to be made in each of the consecutive periods defined by the payment schedule, the “predetermined percentage” is the distribution rate identified in the managed distribution policy, and the value “X” is the number of shares in the hypothetical account. The predetermined percentage may be one of 3%, 5%, or 7%, respectively corresponding to embodiments of fund 100 as Fund A, Fund B, and Fund C.

In a variation of the exemplary embodiment described in the previous paragraph, each of the consecutive periods identified by the managed distribution policy is a fiscal year, and the managed distribution policy identifies that the payments made during each of the fiscal years are to be made monthly. In this variation, the managed distribution policy directs that the monthly distributions per share are to be calculated at the beginning of each fiscal year by averaging the value of the hypothetical shareholder account over a prior three-year period of fund 100 in order to increase the relative predictability and relative stability of the distributions of fund 100 to shareholders from year-to-year. A modified version of the formula is to be used until fund 100 has established three fiscal years of history. Thus, in the first fiscal year of the fund, the monthly per-share distribution is based on the initial account balance of the hypothetical shareholder; in the second fiscal year, the average daily account balance of the hypothetical shareholder over the first fiscal year (or the portion of the first fiscal year for which the fund was in existence) is used to determine the monthly distribution per share; and in the third fiscal year, the average daily account balance of the hypothetical shareholder over the first two fiscal years is used to determine the monthly distribution per share. Finally, in the fourth and subsequent fiscal years, the average daily account balance of the hypothetical shareholder over a prior three-fiscal-year time period will be used to determine the monthly distribution per share.

In a variation of the exemplary embodiments of fund 100 discussed above in which the managed distribution policy sets forth monthly payments to be made over a plurality of consecutive fiscal years, the managed distribution policy calls for the distribution of a targeted amount of cash to be provided to the shareholders of fund 100 on or about the 15th calendar day of each month in a calendar year. The monthly distribution per share for fund 100 in a given calendar year is calculated as of January 1 of that year. The managed distribution policy contemplates that the payments to be provided during a calendar year are fixed during that year, unless there are one or more additional distributions with respect to the same calendar year of fund 100, which would be coincident to the calendar year. The monthly distributions per share for any calendar year, however, are still expected to vary from year-to-year based on the performance of fund 100 during prior years.

Finally, it should again be emphasized that the distribution rates (predetermined percentages) of Funds A, B, and C differ and, therefore, their managed distribution policies differ. The managed distribution policies of Funds A, B, and C specify monthly payments that are to be provided during consecutive calendar years. The monthly payments of Fund A are calculated to equal 1/12th of 3% of the trailing NAV of each share in fund 100 at the time of calculation; the monthly payments of Fund B are calculated to equal 1/12th of 5% of the trailing NAV of each share in fund 100 at the time of calculation; and the monthly payments of Fund C are calculated to equal 1/12th of 7% of the trailing NAV of each share in fund 100 at the time of calculation.

Developing an Investment Portfolio and Managing Fund 100

Continuing with the description of method 200, after establishing the managed distribution policies, investment objectives, investment strategies and performance targets in steps 210-220, processing continues to a step 230 in which the administrator of fund 100 develops investment portfolio 110 based on quantitative analysis and professional judgment, and then continues to a step 240 in which the administrator manages fund 100 and particularly portfolio 110.

Generally, in step 230, the administrator of fund 100 (1) identifies eligible asset classes and investments for fund 100, (2) establishes strategic asset allocation ranges specifying minimum and maximum long-term allocations to eligible asset classes and investments of fund 100 and (3) establishes a short-to-intermediate term asset allocation target for fund 100. The administrator's asset allocation target governs the administrator's day-to-day investment decisions for fund 100 made in step 240.

In step 230, to identify eligible asset classes, the administrator uses quantitative analysis and professional judgment in an attempt to combine complementary asset classes across the risk/reward spectrum. The administrator may combine complementary asset classes with historical correlations to one another that are less than a predetermined threshold set by the administrator in order to generate positive long-term total returns through economic and market conditions with a level of risk less than a threshold determined by the administrator. While managing fund 100 in step 240, the administrator need not maintain a fixed asset allocation policy for fund 100 (although the administrator may adopt such a policy), and the exact proportion of each asset class or investment may be changed to reflect shifts in the administrator's risk and return expectations. In other words, while managing fund 100 in step 240, the administrator is not tied to an asset allocation policy developed in step 230. In summary, the administrator's goal for fund 100 is to construct a broadly diversified portfolio that achieves the investment objective of fund 100.

Method 200 continues to a step 250 in which payments are calculated for each of the periods of fund 100 and provided to shareholders of fund 100 according to the managed distribution policy. As time progresses and after payments are made, further adjustments to the asset allocations of portfolio 110 may be required. Thus, method 200 may loop back from step 250 to step 240 where the administrator may further manage fund 100. Method 200 continues as described above.

Referring now to FIG. 3, there is illustrated an exemplary method 300 for constructing and managing investment portfolio 110 of fund 100, in accordance with an exemplary embodiment of the present invention. Method 300 illustrates steps 210-240 of method 200 in more detail.

Generally, to produce an investment portfolio that has a relatively low probability of year-to-year decline and/or a relatively high probability of maintaining real (rather than nominal) distributions, developing an asset allocation strategy involves dynamically allocating assets across a broadly diversified selection of investment opportunities. The administrator uses quantitative analysis and professional judgment in an attempt to combine complementary asset classes and investments across the risk/reward spectrum. The goal is to construct a broadly diversified portfolio that achieves the investment objective of fund 100. The multi-asset investment strategy of fund 100 is more likely to achieve the investment objective of fund 100 than would a conventional fixed allocation among stocks, bonds, and cash. As noted above, fund 100 may choose from any of the following types of assets or investments (or others): stocks, bonds, cash, money market investments, long/short market neutral investments, absolute return investments, commodity-linked investments, inflation-linked investments, and real estate investments. The administrator of fund 100 constructs the asset allocation strategy to determine the proportions of asset classes and investments that reflect the administrator's evaluation of their expected returns and risks as an integrated whole.

As noted above, fund 100 may invest in both traditional assets (such as stocks, bonds, and money market funds) and non-traditional investments (such as absolute return strategies and alternative asset classes, like commodities). The selection and weighting of asset classes and investments is determined by the asset allocation strategy of fund 100 constructed using method 300. It is contemplated that asset allocation strategies are flexible. Initially, fund 100 may obtain equity and fixed income exposure through index funds, generate long/short market neutral returns through specialized funds designed for this purpose and generally characterized as equity market neutral funds, make absolute return investments directly or through various financial arrangements including shares in a specialized fund designed for this purpose, and gain exposure to the returns of a broad-based selection of commodity futures through futures contracts, commodity-linked swap agreements, commodity-linked structured notes or other commodity-linked derivatives. The asset allocation strategy of fund 100 may change over the life of fund 100 to alter these exposures.

Method 300 begins with a step 310 of generating models of asset classes based on historical investment and macroeconomic behavior. More specifically, step 310 provides historical data for asset classes and outputs the data, which data includes asset class and investment return averages, volatility, and correlations between the modeled asset classes and investments. In a step 320, the administrator reviews these outputted data and makes any adjustments as necessary to the models of the asset classes. In a step 330, projections of the modeled assets classes and investments are generated to estimate future performance of the asset classes and investments.

Processing continues to a step 340 in which method 300 receives various inputs from the administrator of fund 100. Step 340 comprises sub-steps 340A, 340B, and 340C. In sub-step 340A, the administrator specifies an exact payout pattern or spending strategy for fund 100. An example of an exact payout pattern or spending strategy is the managed distribution policy discussed above. In an exemplary embodiment, for the limited purpose of selecting candidate investment portfolios, the distributions of fund 100 under its managed distribution policy and each of the candidate investment portfolios are assumed, in sub-step 340A, (1) to be paid in four equal installments at the end of each quarter of each year, and (2) to sum to 5% of the average balance at the end of the most recent twelve quarters, with the initial year's payments totaling 5% of the initial purchase.

In sub-step 340B, the administrator determines candidate portfolios of investments and/or asset allocation strategies to be modeled, as well as any hard constraints on the investment allocations for portfolio 110. The administrator selects viable candidate portfolios based on a consideration of a wide range of strategic inputs, which may include some combination of the following factors (or others): the prior performance of fund 100; value at risk and expected shortfall; volatility; macroeconomic factors; current and expected market conditions; cash flows; estimates of changes in the spreads between the expected returns of eligible asset classes and investments; historical and expected correlations between and among asset classes and investments; quantitative modeling of the likelihood that a proposed combination of assets and investments will achieve the investment objective of fund 100; and the results of stress tests.

Finally, in sub-step 340C, the administrator determines the quantitative objectives to be optimized for candidate portfolios for consideration for selection as portfolio 110 of fund 100. Examples of quantitative objectives that the administrator may specify in sub-step 340C include: median simulated real geometric mean return over 30 years, median simulated real geometric mean growth in simulated distributions over 30 years, median simulated nominal geometric mean growth in simulated distributions over 30 years, median simulated real geometric mean growth in simulated distributions over 30 years, estimated probability of a 5% year-to-year decline in simulated nominal payments, estimated probability of 3 consecutive years of a 5% or more decline in simulated nominal payments over a 30-year history, estimated probability of maintaining nominal value of simulated nominal payments over a set period, and estimated probability of maintaining real value of simulated nominal payments over a set period.

Continuing with the description of method 300, in a step 350, the administrator uses a simulation to identify candidates for portfolio 110. Particularly, the simulation uses the data supplied by the administrator in sub-steps 340A-C and the results provided by step 330 to optimize construction of portfolio 110 across multiple asset classes and investments. In an exemplary embodiment, the simulation is a regression-based Monte Carlo simulation that runs a large number of cycles on each possible portfolio, with each run simulating long-term future performance. While particular types of simulations may be considered superior to others and the overall performance of fund 100 may be highly dependent on the robustness of the simulation performed, the present invention is not limited to or dependent upon the use of any particular type of simulation. The results, i.e., the modeled portfolios and asset allocations, of the capital markets simulation model are outputted and plotted in a step 360.

Referring now to FIG. 4, there are illustrated exemplary results plotted in step 360, which results are provided by the simulation performed in step 350. Each portfolio is plotted by its probability of maintaining real spending power after 20 years and its probability of a 5% decline in payments from one year to the next. Optimal portfolios lie along the upper frontier of plot 400, as they have the greatest probability of maintaining real spending power after 20 years given a particular probability of a 5% decline from one year to the next. Although not illustrated, it is also contemplated that plot 400 may plot probability of maintaining nominal spending power after 20 years rather than real spending power.

Continuing again in method 300 illustrated in FIG. 3, after the results of the capital markets simulation model are plotted in step 360, processing continues to a step 370. In step 370, the administrator chooses an investment portfolio from the modeled results plotted by probability of year-to-year decline versus probability of maintaining real distributions greater than a predetermined probability. The administrator therefore selects an investment portfolio from the upper “efficient” frontier of plot 400, from candidate investment portfolios having a relatively low probability of year-to-year decline and/or a relatively high probability of maintaining real distributions. Embodiments in which the administrator considers probabilities of maintaining nominal spending power rather than real spending power are also contemplated.

Finally, in step 380, the advisor seeks to manage fund 100 consistent with a variety of statistical and compliance-based risk management controls and procedures. As the administrator manages fund 100 according to the calculated asset allocation strategy in step 380, the administrator of fund 100 may alter the asset allocation strategy at any time to incorporate additional asset classes or investments into portfolio 110 or to change the weightings of asset classes and investments represented in portfolio 110 in an effort to reduce overall risk or improve risk-adjusted returns consistent with the investment objective of fund 100. The administrator of fund 100 may use the capital markets simulation model described above to generate revised forward-looking asset class and investment performance expectations for optimization of portfolio 110 at any time during the life of fund 100. More specifically, the administrator may model a plurality of additional candidate investment portfolios and choose a reallocated investment portfolio from the modeled results that is expected to have a relatively low probability of year-to-year decline and a relatively high probability of maintaining real or nominal distributions. Thus, the administrator may re-optimize the asset allocation strategy of fund 100, and therefore the asset allocation of portfolio 110 of fund 100, at any time.

The managed distribution policy of fund 100 is not supported by any form of guarantee, line of credit, credit support or any other form of financing intended to guarantee distributions or investment performance to shareholders. Instead, fund 100 makes distributions in accordance with its managed distribution policy, with the result that distributions are likely to vary over time. Accordingly, investors in fund 100 may see their year-to-year distributions grow or decline roughly in tandem with average fund performance over a trailing 3-year period (subject to the terms and conditions of the managed distribution policies). The results of the administrator's investment models, however, indicate that fund 100, and therefore the accounts of the investors in fund 100, are not likely to run out of money over time. Of course, fund 100 may experience losses, in which case the automated payout mechanism may cause investors to consume a corresponding portion of their principal over time. Other embodiments of fund 100 in which fund 100 does guarantee that the managed distributions will be met are contemplated.

As noted above, fund 100 may be embodied as one of Funds A-C. Each of Funds A-C is targeted to appeal to a different set of investors, although some overlap is possible. It should be noted that Funds A-C may attract assets from outside of the retirement channel, given the focus of Funds A-C on regular cash flows and principal preservation.

Fund A is expected to have the greatest appeal to retirement investors who seek only a modest current payout from their assets, but who wish to see their payouts and capital increase over time. Fund A is expected to sustain a managed distribution policy with a 3% annual distribution rate. Compared to the other subject funds, Fund A has a high probability of generating growth in both capital and payouts that exceeds inflation. If successful, Fund A should provide long-term capital appreciation.

Fund B is likely to appeal to retirement investors who want to balance a need for a current payout from their assets with a desire to maintain the purchasing power of their payouts and capital over the long term. Fund B is expected to sustain a managed distribution policy with a 5% annual distribution rate, while providing inflation protection and capital preservation over the long term.

Fund C is likely to appeal to retirement investors who require a greater payout level to satisfy current spending needs. Fund C is expected to sustain a managed distribution policy with a 7% annual distribution rate. Although the payouts and capital of Fund C are not expected to grow at a rate that keeps pace with inflation, Fund C does seek to preserve the “nominal” (or original) value of invested capital over the long term.

Although specific embodiments are described herein comprising Fund A, Fund B, and Fund C, it should be understood that the funds may be offered with any incremental annual distribution rate that has a reasonable probability of providing the targeted returns. Furthermore, although several exemplary embodiments of fund 100 are described above as computing payments based on the average daily account balance of hypothetical shareholder over three calendar years, different time periods may also be used.

As noted above, in an exemplary embodiment of method 300, the simulation performed in step 350 is a regression-based Monte Carlo simulation. Such an embodiment of method 300 uses the regression-based Monte Carlo simulation to advantage over conventional simulation tools, such as historical time-pathing and basic Monte Carlo simulation.

Historical time-pathing consists of generating future return scenarios based on an asset's historical returns over a chosen time period. Since this historical analysis is restricted to the observed historical sequence outcomes, each scenario simply starts at a different date. A limitation with this approach is that it can exclude extreme-tailed possibilities (rare events never recorded in the historical data sample that could have occurred).

In basic Monte Carlo simulation, return scenarios are drawn from a selected probability distribution of outcomes, rather than replicating chronological segments of historical series. In essence, an asset's simulated return at any point in time will equal its long-term average return plus or minus “noise,” the magnitude of which is dictated by the historical volatility of the asset. Although popular among certain investment professionals, basic Monte Carlo techniques have their own limitations. Often, basic Monte Carlo tools assume that asset returns are uncorrelated with the assets' own past returns (i.e., not serially correlated returns) and that correlations with other asset returns in the portfolio are fixed (i.e., fixed cross-correlations among asset returns).

Referring now to FIG. 5, there is illustrated a capital markets model 500, in accordance with an exemplary embodiment of the present invention. Capital markets model 500 is used to perform steps 310, 330, and 350 of method 300.

Capital markets model 500 is based on the theoretical notion that the returns of various asset classes reflect the compensation investors receive for bearing different types of systematic risk (or beta). To reasonably forecast the potential distribution of future asset returns, capital markets model 500 is designed to identify the primary macroeconomic and financial risk factors and how they influence asset returns over time.

Using a long span of monthly financial and economic data, capital markets model 500 estimates a dynamic statistical relationship between risk factors and asset returns. In an exemplary embodiment, capital markets model 500 uses regression-based Monte-Carlo simulation methods to project these relationships in the future.

The return-forecast portion of capital markets model 500 involves three fundamental processes, as illustrated in FIG. 5: (1) a core module 510, (2) an attribution module 520, and (3) a simulation module 530.

Core module 510 implements a dynamic statistical model of global macroeconomic and financial risk factors. Its main function is to generate forecasts of these economic and financial risk factors over different time horizons. In an exemplary embodiment of capital markets model 500, core module 510 implements a vector autoregressive model (VARM). In this embodiment, the VARM measures the interrelationship of the various risk factors with each other. This process begins with the VARM estimating relationships (more specifically, regression “betas”) among the system of risk factors based on historical data. The module can then be used to project the estimated relationships into the future over any time horizon. An exemplary time horizon is ten years or longer.

Exemplary risk factors used by core module 510 include the following:

1. Global equity factors: These risk factors are the core drivers of asset prices that are linked to the performance of both domestic and international stock markets.

2. Global fixed income factors: This group of risk factors includes the primary ones that account for all of the stylized characteristics of the global term structure of interest rates or yield curves. The yield curve is considered a leading indicator of economic activity and inflation expectations. International fixed income factors capture differences in long-run inflation expectations between the U.S. bond market and major foreign governments' bond markets, as well as differences in the expected rate of real economic growth and monetary policy. It is important to note that the fixed income factors within core module 510 permit the generation of a complete term structure of U.S. and international government bond yields (ranging from one month to 30 years in duration) for every model simulation at every future point in time.

3. Global economic factors: These risk factors capture current business conditions, inflation shocks, and realized fluctuations in the global business cycle. Global economic and financial conditions are also summarized by commodity markets and foreign exchange markets indicators. For instance, currency risk factors help to explain differences in realized returns between U.S. and unhedged international assets.

A benefit of core module 510 is that it models all of these exemplary global financial and economic risk factors collectively and dynamically using a regression-based framework. Consequently, each of these three risk-factor groups is important to the accuracy of the forecasts of capital markets model 500.

Attribution module 520 relates the global economic and financial risk factors to the returns of various asset classes, including international equities. The main function of attribution module 520 is to “map” the returns of those asset classes to contemporaneous changes in the core global risk factors. This mapping is based on observed historical relationships and is estimated using regression techniques.

For example, attribution module 520 may include the return differential between unhedged international equities and domestic equities. Attribution module 520 captures some of the variability in this return differential based on patterns in certain global equity risk factors, changes in the shapes of the U.S. and international yield curves, and fluctuations in the value of the U.S. dollar, among other factors.

Simulation module 530 constructs scenarios for all risk factors and asset classes represented in modules 510 and 520. Simulation module 530 creates a distribution of future returns, volatilities, and correlations 540. In other words, it simulates a broad range of possible asset-return outcomes (as opposed to a single-point forecast). In this way, simulation module 530 and, therefore, capital markets model 500 account for the volatility of asset return forecasts.

As noted above, in an exemplary embodiment, capital markets model 500 (specifically, simulation module 530) follows a regression-based Monte Carlo simulation method. In a further exemplary embodiment, the vector autoregressive model of core module 510 is combined with a Monte Carlo approach.

As previously discussed, a regression-based Monte Carlo method is an effective way to incorporate statistical uncertainty into forecasts. A sensible approach for dealing with statistical uncertainty is an important piece of any analytical model, since the model needs to provide investors with an adequate framework to assess unanticipated risks. In an exemplary embodiment, for each quarter in the forecast horizon, capital markets model 500 simulates 10,000 scenarios, yielding a complete distribution of potential future paths for the various risk factors and asset returns at various forecast horizons.

FIG. 6 illustrates exemplary distributions of outcomes generated by simulations of capital markets model 500 for selected asset classes (U.S. intermediate-term bonds and U.S. equities), in accordance with an exemplary embodiment of the invention. Although not illustrated in FIG. 6, the outputs of simulations can also be summarized in reports containing key statistical characteristics of the simulated data. An array of summary statistics, including means, medians, and standard deviations, may be tabulated for the various asset-class returns at various forecast horizons.

The execution of model 500 can be divided into two phases. A first phase includes the three modules as previously described: core module 510, attribution module 520, and simulation module 530. The final outcome of this first phase is the distributions of returns and volatilities 540 at the level of each asset class. The second phase consists of combining the asset classes' simulations to create a full set of potential investment portfolios to be considered. Thus, the simulation output from model 500 forms the basis for further analysis and simulations at the portfolio level. Outcomes are combined with exemplary objectives, risk tolerance, and investment horizon of the fund.

It should be understood that some or all of the steps of methods 200 and 300 and some or all of the functionality (modules) of capital markets model 500 may be carried out by or with the assistance of a computer, including but not limited to automated processes for the following: (i) all or any portion of the fund management processes; (ii) issuing, buying, and selling of shares and underlying securities; (iii) receiving and transmitting transfers to and from financial institutions for the purchase or shares or the distribution of periodic payments to shareholders; (iv) calculating the amount of periodic distributions; (v) computerized accounting; (vi) computerized receipt and storage of shareholder data; (vii) computerized reporting to shareholders; and (viii) other computerized or automated functions comprised within the management, distribution, servicing, and other activities in connection with fund 100 and model 500. It should also be understood that the programming techniques necessary to automate such steps and modules by computer are well known in the art.

Although the invention is illustrated and described herein with reference to specific embodiments, the invention is not intended to be limited to the details shown. Rather, various modifications may be made in the details within the scope and range of equivalents of the claims and without departing from the invention. 

1. A method of administering an investment fund, the method comprising: creating a plurality of shares in the investment fund for sale; providing a managed distribution schedule comprising a plurality of consecutive periods, a number of payments to be provided during each of the consecutive periods, and a formula for calculating a value for each of the payments, the value comprising 1/n^(th) of a predetermined percentage of a designated value corresponding to one of the plurality of shares, wherein n equals a number of payments and the designated value for at least one of the consecutive periods comprises a trailing Net Asset Value (NAV); providing an investment strategy for investing in assets to provide funds sufficient to meet the managed distribution schedule, the assets composing an investment portfolio; issuing at least one share to an investor in exchange for funds received from the investor; investing the received funds according to the investment strategy; calculating the value of each of the payments to be provided according to the managed distribution schedule in a period; and providing each of the payments to the investor during the period.
 2. The method of claim 1, wherein the trailing NAV is calculated by averaging NAV over a predetermined amount of time.
 3. The method of claim 1, wherein the investment strategy is designed to preserve a value of the assets, as a whole, on a real or nominal basis.
 4. The method of claim 1, wherein the investment strategy is designed to achieve a long-term performance target.
 5. The method of claim 1, wherein each of the periods comprises a year and n=12.
 6. The method of claim 5, wherein: for a first year of the investment fund, the designated value comprises an initial per-share value, and for a second year and subsequent years of the investment fund, the designated value comprises a trailing NAV calculated using an averaged daily per-share NAV over at least a portion of years of the investment fund prior to the second or subsequent years.
 7. The method of claim 6, wherein for a third year of the investment fund, the designated value comprises an averaged daily per-share NAV over at least a portion of the first and second years of the investment fund.
 8. The method of claim 6, wherein for a fourth year or subsequent years of the investment fund, the designated value comprises an averaged daily per-share NAV over at least a portion of three years of the investment fund previous to the fourth or subsequent years.
 9. The method of claim 1, wherein the step of providing the investment strategy comprises selecting an asset allocation strategy chosen from an efficient frontier of modeled asset allocation strategies plotted by probability of year-to-year decline and probability of maintaining real or nominal distributions.
 10. The method of claim 1, further comprising: periodically modeling historical results of asset classes and investments represented in the investment portfolio and asset classes and investments not represented in the investment portfolio; adjusting the asset allocation strategy of the investment portfolio to a revised group of asset classes and investments; and reinvesting or rebalancing the investment portfolio according to the adjusted asset allocation strategy. 